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About

Sivakumar Rathinam is a prominent robotics and autonomous systems researcher whose work spans path planning, multi-agent coordination, and unmanned vehicle routing. His research addresses some of the most computationally challenging problems in autonomous navigation, with particular focus on Dubins path optimization for fixed-wing UAVs and ground robots, and multi-agent path finding (MAPF) in complex environments. Rathinam has made significant contributions to bounding and approximating shortest Dubins paths through waypoint sequences, work that has attracted over 75 citations across two complementary studies and directly informs mission planning for constrained autonomous vehicles. His development of conflict-based search frameworks for multi-objective and combinatorial MAPF problems represents a major advance in coordinating multiple robots simultaneously under competing real-world constraints like fuel consumption and completion time, garnering over 90 citations combined. His CBSS algorithm extended classical MAPF to handle unassigned targets, addressing a critical gap for warehouse and logistics robotics applications. With research touching UAV recharging coordination, dynamic obstacle avoidance, and machine learning-augmented routing heuristics, Rathinam's portfolio reflects both theoretical rigor and practical relevance. His cumulative impact, exceeding 270 citations, establishes him as an influential voice shaping the future of intelligent autonomous systems.